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Power and sample assessments for tests of hypotheses on cost‐effectiveness ratios

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  • Joseph C. Gardiner
  • Marianne Huebner
  • James Jetton
  • Cathy J. Bradley

Abstract

We address the issue of statistical power and sample size for cost‐effectiveness studies. Tests of hypotheses on the cost‐effectiveness ratio (CER) are constructed from the net cost and incremental effectiveness measures. When the difference in effectiveness is known, we derive formulae for statistical power and sample size assessments for one‐ and two‐sided tests of hypotheses of the CER. We also construct a test of the joint hypothesis of cost‐effectiveness and effectiveness and derive an expression connecting power and sample size. Our methods account for the correlation between cost and effectiveness and lead to smaller sample size requirements than comparative methods that ignore the correlation. The implications of our formulae for cost‐effectiveness studies are illustrated through numerical examples. When compared with trials designed to demonstrate effectiveness alone, our results indicate that a trial appropriately powered to demonstrate cost‐effectiveness might require sample sizes many times greater. Copyright © 2000 John Wiley & Sons, Ltd.

Suggested Citation

  • Joseph C. Gardiner & Marianne Huebner & James Jetton & Cathy J. Bradley, 2000. "Power and sample assessments for tests of hypotheses on cost‐effectiveness ratios," Health Economics, John Wiley & Sons, Ltd., vol. 9(3), pages 227-234, April.
  • Handle: RePEc:wly:hlthec:v:9:y:2000:i:3:p:227-234
    DOI: 10.1002/(SICI)1099-1050(200004)9:3<227::AID-HEC509>3.0.CO;2-Z
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    File URL: https://doi.org/10.1002/(SICI)1099-1050(200004)9:33.0.CO;2-Z
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    References listed on IDEAS

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    1. Tambour, Magnus & Zethraeus, Niklas & Johannesson, Magnus, 1997. "A Note on Confidence Intervals in Cost-Effectiveness Analysis," SSE/EFI Working Paper Series in Economics and Finance 181, Stockholm School of Economics.
    2. Daniel Polsky & Henry A. Glick & Richard Willke & Kevin Schulman, 1997. "Confidence Intervals for Cost–Effectiveness Ratios: A Comparison of Four Methods," Health Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 243-252, May.
    3. Maiwenn J. Al & Ben A. Van Hout & Bowine C. Michel & Frans F.H. Rutten, 1998. "Sample size calculation in economic evaluations," Health Economics, John Wiley & Sons, Ltd., vol. 7(4), pages 327-335, June.
    4. Andrew R. Willan & Bernie J. O'Brien, 1999. "Sample size and power issues in estimating incremental cost‐effectiveness ratios from clinical trials data," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 203-211, May.
    5. Andrew H. Briggs & David E. Wonderling & Christopher Z. Mooney, 1997. "Pulling cost‐effectiveness analysis up by its bootstraps: A non‐parametric approach to confidence interval estimation," Health Economics, John Wiley & Sons, Ltd., vol. 6(4), pages 327-340, July.
    6. Eugene M. Laska & Morris Meisner & Carole Siegel, 1997. "Statistical Inference for Cost–Effectiveness Ratios," Health Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 229-242, May.
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    Cited by:

    1. William Hollingworth & Richard A. Deyo & Sean D. Sullivan & Scott S. Emerson & Darryl T. Gray & Jeffrey G. Jarvik, 2002. "The practicality and validity of directly elicited and SF‐36 derived health state preferences in patients with low back pain," Health Economics, John Wiley & Sons, Ltd., vol. 11(1), pages 71-85, January.

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